Identifying Genes Relevant to Specific Biological Conditions in Time Course Microarray Experiments

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Identifying Genes Relevant to Specific Biological Conditions in Time Course Microarray Experiments

Microarrays have been useful in understanding various biological processes by allowing the simultaneous study of the expression of thousands of genes. However, the analysis of microarray data is a challenging task. One of the key problems in microarray analysis is the classification of unknown expression profiles. Specifically, the often large number of non-informative genes on the microarray a...

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Statistical tests for identifying differentially expressed genes in time-course microarray experiments

MOTIVATION Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time, we are interested in testing gene expression profiles for different experimental groups. However, no sophisticated analytic methods have yet been proposed to handle time-course experiment data. RESULTS We...

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Identifying differentially expressed (DE) genes across conditions or treatments is a typical problem in microarray experiments. In time course microarray experiments (under two or more conditions/treatments), it is sometimes of interest to identify two classes of DE genes: those with no time-condition interactions (called parallel DE genes, or PDE), and those with time-condition interactions (n...

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Significance analysis of time course microarray experiments.

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ژورنال

عنوان ژورنال: PLoS ONE

سال: 2013

ISSN: 1932-6203

DOI: 10.1371/journal.pone.0076561